With the transition from analog to a digital imaging, digital radiographic systems have been adopted by the medical imaging community and now represent the standard of care at many hospitals and imaging centers. Among other advantages, digital radiographic imaging has an expanded dynamic range, with the potential for providing much richer information about anatomic structures for image diagnosis than is available using conventional analog radiographic images. However, this expanded capability brings with it some additional complexity, requiring image processing that is capable of handling the digital radiographic image data in order to best render the image for diagnostic use. One method for diagnostic image rendering is taught, for example, in commonly assigned U.S. Pat. No. 7,266,229 entitled “Method for Rendering Digital Radiographic Images for Display Based on Independent Control of Fundamental Image Quality Parameters” to Couwenhoven et al.
As part of the diagnostic procedure, it can be helpful to present, in a consistent manner, images of the same patient anatomy but taken at different times, at different stages of treatment, or on different imaging systems. One approach is to normalize the image representation, as described in U.S. Pat. No. 7,321,674 entitled “Method of Normalising a Digital Signal Representation of an Image” to Vuylsteke. In this process, a normalization parameter is derived from the image content itself and applied to normalize the image data accordingly.
Consistent rendering, as taught in the Couwenhoven et al. '229 patent and as applied in the example embodiment described in the Vuylsteke '674 disclosure, can be but one of a number of aspects of image rendering that are of particular interest for diagnostic review and assessment. While there can be value for consistent rendering in some applications, other imaging situations benefit more from a proper choice of suitable parameters that show particular details of the image content more effectively for diagnosis. Thus, other image rendering goals can be to maximize global or detail-related contrast, brightness, and sharpness, for example, which may override image consistency considerations.
Approaches have been proposed for evaluating image quality of diagnostic images, directed to identifying quality problems detected by expert observers or trained expert systems, maintaining statistical data on technologist and practitioner performance, and determining whether or not the overall image quality is sufficient for diagnostic purposes. However, these conventional solutions go no further than providing some base-level assurance of image quality, accumulating metrics that relate to various image quality characteristics as a measure of overall acceptability for diagnosis.
Provided that at least rudimentary image quality is achieved, an aspect of diagnostic value for digital x-rays and other diagnostic images relates to image presentation, that is, to how the image data is rendered for display to the clinician. Viewer preference plays an important part in how effectively the digital image can be used, as is acknowledged in commonly assigned U.S. Pat. No. 7,386,155 entitled “Transforming Visual Preference Terminology for Radiographic Images” to Foos et al. A specific practitioner may have preferred settings for image characteristics such as brightness, sharpness of detail, contrast, and latitude, for example. Values for these image characteristics can be adjusted over a range of settings according to how the image is rendered. Although some diagnostic display systems may allow viewer adjustment of rendering parameters from one image to the next, this adjustment and rendering processing takes time and it can be burdensome to the radiologist workload to make adjustments to individual images in order to suit viewer preferences.
Thus, it can be appreciated that there would be advantages to a diagnostic imaging system that allows a measure of flexibility in rendering and in the specification of how the image is to be presented for diagnosis, and that allows automated and easily customized rendering for different viewers or for different types of images.